Title :
Independent Task Scheduling by Artificial Immune Systems, Differential Evolution, and Genetic Algorithms
Author :
Krömer, Pavel ; Plato, Jan ; Snasel, Vaclav
Author_Institution :
Fac. of Electr. Eng. & Comput. Sci., VSB-Tech. Univ. of Ostrava, Ostrava-Poruba, Czech Republic
Abstract :
Scheduling is one of the core steps to efficiently exploit the capabilities of heterogeneous distributed computing systems and it is also an appealing NP-complete problem. There is a number of heuristic and metaheuristic algorithms that were tailored to deal with scheduling of independent jobs. In this study we investigate the efficiency of three bio-inspired metaheuristics for finding good schedules of independent tasks.
Keywords :
artificial immune systems; computational complexity; distributed processing; genetic algorithms; scheduling; NP-complete problem; artificial immune systems; bioinspired metaheuristics; differential evolution; genetic algorithms; heterogeneous distributed computing systems; independent task scheduling; Genetic algorithms; Immune system; Processor scheduling; Schedules; Sociology; Statistics; Vectors; artificial immune systems; differential evolution; genetic algorithms; independent task scheduling; machine learning;
Conference_Titel :
Intelligent Networking and Collaborative Systems (INCoS), 2012 4th International Conference on
Conference_Location :
Bucharest
Print_ISBN :
978-1-4673-2279-9
DOI :
10.1109/iNCoS.2012.76
